Hackathon for improved diagnosis of cardiovascular diseases

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Medical specialists and researchers from the University Medical Center Utrecht (UMC Utrecht) will be working together with ABN AMRO’s data analysts to find a better method of detecting severe cardiovascular disorders. The collaborative effort, or ‘hackathon’, will be held in Utrecht from 21 to 25 January. The specialists will analyse a large amount of data gathered by UMC Utrecht in recent years. They will try to find out whether there is a relationship between the results of simple medical tests such as ECGs and the results of further tests such as MRIs. Their goal is to find an algorithm showing that a person with complaints has (or does not have) disorders of the heart’s major or minor arteries.

Previous successes

Hackathons held during the Beyond Banking Days successfully found predictive algorithms for the treatment of cancer. If this hackathon is also successful, a validation period will follow. The participants in the hackathon will then have to establish with certainty whether the algorithm has predictive power.

Major and minor arteries

Simple tests such as ECGs can be used to detect damage to major arteries, but damage to minor arteries is difficult to detect with existing diagnostic methods. At the same time, we see that diagnostic tests tend to perform less well among women. The analysis will factor in differences between men and women. An algorithm is expected to improve the diagnosis of cardiovascular diseases, especially among women.

Benefits

The benefits are multiple. Making the right diagnosis in patients with cardiovascular disorders is often difficult as complaints may be vague and it’s not always clear that the complaints could be symptoms of heart failure. Additionally, it can be difficult for doctors to determine that something is wrong with a patient’s heart or arteries. And so some patients are sent home after an ECG only to find out later that they do have a heart condition.

A reliable algorithm can help detect possible disorders, so that further tests and treatment can be performed at an earlier stage. Conversely, some patients now undergo tests, such as an MRI, which later appear to have been unnecessary because there was nothing the matter with them. MRIs are relatively expensive and time-consuming for hospital staff. Although this cannot always be prevented, a reliable algorithm could bring considerable savings for hospitals.

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